Investigates nonlinear controllers with dynamic compensation depending solely on the desired state and velocity computed from the position signal using a velocity observer. A feedforward controller and a controller similar to the computed torque controller are compared. The stability is proved, and adaptive versions of these two controllers are implemented on a 6 DOF parallel manipulator with uncoupled and highly nonlinear dynamics. Both controllers improved the tracking performance critically relative to a linear controller. We recommend using the feedforward controller, because it is simpler to implement and the difference of performance between both controllers is minor.

In tunneling and mining construction work, heavy and large manipulators are used to spray liquid concrete on the walls. These manipulators are usually operated manually with simple units allowing control of all actuators independently. In cooperation between industry and university, a novel control system has been developed for the redundant heavy manipulator Robojet(R) that supports the operator by calculating the inverse kinematic model and controlling all actuators automatically. The paper presents the solution of the redundant inverse kinematics of the Robojet using the null-space method and its implementation in a control system.

In this paper, 2 control algorithms for learning and compensating for the dynamics of manipulators during the motion are presented and tested experimentally. It is shown that the adaptive feedforward controller (AFFC) is well suitable for learning the parameters of the dynamic equation, even, in presence of friction and noise. The resulting control performances are better than with measured parameters for any trajectory in the workspace. When the task consists of driving a repeated trajectory, an adaptive look-up-table MEMory, introduced and analyzed in this paper, is however simpler to implement and results in even better control performances.

In order to identify the dynamic parameters in nonlinear adaptive control the robot's dynamic equation has to be written in a linear form. Many methods have been proposed for serial robots, but for parallel robots, the few solutions proposed so far lead to complicated equations that are not readily usable for real-time implementation. In this paper we propose a new method based on the virtual work principle to find a linear form of the dynamic equation of robots. Compared to other methods, it has the advantage that it does not need to open the closed loop structure into a tree-structure robot. It considers rather each body separately using its Jacobian matrix to project the forces into the joint space of the robot. Thus, simplification can be made at the very beginning of the modeling. This is very efficient when used to model fully parallel robots. As an illustration, the proposed method is applied to the 3dof DELTA parallel robot.

This paper presents the dynamic equation, nonlinear control and dynamic parameters identification of the Hexaglide, a new 6-DOF parallel manipulator intended to be used as a high speed milling machine. Using a method based on the virtual work principle, the dynamic equation is found in a compact linear form and then used in a nonlinear adaptive control algorithm based on the minimization of the tracking error. The dynamic parameters are learned during motion and introduced in an inverse dynamic model used as a feedforward compensator. Specific trajectories, exciting the parameters separately, enable a fast stepwise learning of the 12 parameters. A simulation demonstrates the validity of the approach.

Operating a robot in the micro/nano-world presents challenges not found in the macro world. This paper presents a graphical user interface for a robot which manipulates objects in the micro world, developed at the Swiss Federal Institute of Technology Zurich. The robot, which works under a microscope, was designed to perform operations with nanometer resolution. To enable the operator to manipulate objects with the robot, he is provided with a set of visualization and manipulation tools. The visualization tools are: a live microscope video image capable of both mono and stereo viewing modes, and a 3D virtual solid model of the robot with perspective as well as orthogonal views available at the same time. The manipulation tools are: a control panel used to check the status and to operate both the camera and the robot itself and an interface with a 6 degree of freedom spacemouse. This paper describes the robot system, the visualization and manipulation tools, and presents some field test results and conclusions on the implementation of this user interface.

The recent development of the direct drive DELTA, a 3 to 4 degree-of-freedom parallel robot dedicated to pick and place operations, opened a number of new perspectives in the domain of fast and accurate handling of light objects. The elimination of reduction gearing in these designs although improving acceleration capabilities has the disadvantage of increasing mechanical couplings between robot axes and reflects the full varying inertias directly onto each motor axis. To resolve this problem, the computed-torque control method has been applied to many serial robots over the past few years. Its application to parallel robots has however been restrained by the difficulty in establishing a simple dynamic model that can easily be calculated in real time. In this paper, an efficient method based on the direct application of the virtual work principle is proposed. Contrarily to the other methods developed up to now, it has the advantage of providing explicitly the mass matrix of the robot, which can be used in the control algorithm for axes decoupling. The use of the dynamic model in a feedforward control strategy leads to an improvement of trajectory tracking by a factor 6.

In this paper the vision-based control of a microrobot operating under a light microscope is presented. For high accuracy manipulation the parameters describing the relationship between the reference frame and the frame attached to the robot must be continuously and accurately updated These parameters are unknown a priori and are not directly measurable, but can be deduced by observing the scene change during the motion. The relative positioning accuracy is about 100 nm and trajectories can be precisely followed in 3 degrees of freedom. Experimental results are presented.

Nanotechnology is a key issue in today's and tomorrow's development of advanced products. Soon new tools will be needed to automatically handle and assemble micro-sized objects with nanometer precision, or simply to give human beings the capability of operating in these tiny dimensions. In view of the emerging applications in this field, the Swiss Federal Institute a Technology, Zurich (ETHZ) decided to focus on an interdisciplinary project with the theme "Nanorobotics", i.e. automated handling of microparts with nanometer resolution. After a short description of the goals and the approach taken in this project this paper focuses on some important aspects of the design of high precision robots. Two new 3 DOF planar robots are presented. Both of them have an unlimited range of motion while having a resolution down to 10 nm. They have been controlled using vision feedback under a light microscope and have shown very promising results.